Phase 5: 3D Generation · 45 min · Python · Tripo API

3D Generation Modes

Text-to-3D for concepts, image-to-3D for products, multi-view for photorealism — each mode serves a different production need.

Real-world application: Knowing all 3D generation modes and when to use each demonstrates practical 3D generation engineering skills.

What you will learn

Implement text-to-3D: generate 3D model from text description
Implement image-to-3D: generate 3D model from a single or multiple 2D images
Understand multi-view reconstruction: multiple angles → 3D model
Understand Gaussian Splatting: radiance field representation for photorealistic 3D

Objective

Inspect generated assets as usable geometry, materials, and motion—not merely attractive previews. In the paired studio lab, build a pipeline that: (1) generates an image with FLUX, (2) converts the image to a 3D model using Tripo's image-to-3D API, (3) exports the model in GLB format. Track cost and generation time for each stage.

The Problem

A team needs a 3D model of a specific product (a red coffee mug with a handle). They use text-to-3D with the prompt "a red coffee mug with a handle." The result looks like a mug, but it's not their mug — the shape is different, the handle is wrong, the proportions are off. They don't realize that image-to-3D would have used a photo of their actual mug to generate an accurate 3D model.

Each 3D generation mode serves a different production need. Knowing when to use each demonstrates practical 3D generation engineering skills.

What you'll build
Implement text-to-3D, image-to-3D, and multi-view reconstruction using the Tripo API. Understand Gaussian Splatting for photorealistic 3D. Document when to use each mode.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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